Journal ArticleDOI
River flow forecasting through conceptual models part I — A discussion of principles☆
J.E. Nash,J.V. Sutcliffe +1 more
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TLDR
In this article, the principles governing the application of the conceptual model technique to river flow forecasting are discussed and the necessity for a systematic approach to the development and testing of the model is explained and some preliminary ideas suggested.About:
This article is published in Journal of Hydrology.The article was published on 1970-04-01. It has received 19601 citations till now. The article focuses on the topics: Conceptual model & Flood forecasting.read more
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Application of the Artificial Neural Network model for prediction of monthly Standardized Precipitation and Evapotranspiration Index using hydrometeorological parameters and climate indices in eastern Australia
Ravinesh C. Deo,Mehmet Şahin +1 more
TL;DR: In this paper, the authors tested the feasibility of the ANN as a data-driven model for predicting the monthly Standardized Precipitation and Evapotranspiration Index (SPEI) for eight candidate stations in eastern Australia using predictive variable data from 1915 to 2005 (training) and simulated data for the period 2006-2012.
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Improved annual rainfall-runoff forecasting using PSO-SVM model based on EEMD
TL;DR: In this article, an adaptive data analysis methodology, ensemble empirical mode decomposition (EEMD), is presented for decomposing annual rainfall series in a rainfall-runoff model based on a support vector machine (SVM).
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Comparative assessment of predictions in ungauged basins – Part 1: Runoff-hydrograph studies
Juraj Parajka,Juraj Parajka,Alberto Viglione,Magdalena Rogger,Jose Luis Salinas,Murugesu Sivapalan,Günter Blöschl +6 more
TL;DR: In this article, the authors compare studies predicting runoff hydrographs in ungauged catchments and compare the differences in performance in terms of the underlying climate and landscape controls.
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River Stage Forecasting in Bangladesh: Neural Network Approach
TL;DR: A relatively new approach, artificial neural network, was demonstrated in this article to be a highly suitable flow prediction tool yielding a very high degree of water-level prediction accuracy at Dhaka, Bangladesh, even for up to 7 lead days.
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Impacts of input parameter spatial aggregation on an agricultural nonpoint source pollution model
T.W FitzHugh,D.S Mackay +1 more
TL;DR: In this article, the authors used the Soil and Water Assessment Tool (SWAT), a distributed-parameter agricultural nonpoint source pollution model, to investigate how the size or number of subwatersheds used to partition the watershed affect model output, and what are the processes responsible for model behavior.